Signal clipping distortion audit calculator

Calculate clipped samples and clipped fraction with your own figures.

Your numbers

Use the units shown. Results update as you change valid inputs.

Use clipped samples and clipped fraction to compare changes to your inputs. The method and limits below explain the scope.

Examples

Examples

Try the starting example

Samples
-2,-0.5,0,0.5,2
Lower bound
-1
Upper bound
1
Clipped samples
[-1,-0.5,0,0.5,1]
Clipped fraction
0.4
Clipped run index ranges
[[0,0],[4,4]]

Try another scenario

Samples
[-3, -2, 0.1, 2, 3]
Lower bound
-1
Upper bound
1
Clipped samples
[-1,-1,0.1,1,1]
Clipped fraction
0.8
Clipped run index ranges
[[0,1],[3,4]]
Calculation method

Calculation method

Clipped samples

Clamp each sample to supplied bounds.

Clipped fraction

Count samples strictly outside bounds / count.

Clipped run index ranges

Inclusive zero-based start/end of consecutive clipped samples.

Symbols and units
a
Samples
b
Lower bound
c
Upper bound

Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.

Assumptions & limits

Assumptions & limits

  • Samples, full-scale bounds. Returns Clipped fraction and clipped runs. All coefficients and observations are user supplied; results describe only the stated mathematical model. Quantities are deterministic calculations from supplied observations and assumptions; no external data is fetched. Supported limits: Finite inputs only; numeric fields bounded as labelled. Lists and JSON records are limited to 256 entries unless a stricter tool bound is stated. No automatic design approval, legal conclusion, treatment recommendation or safety certification. Samples: minimum None, maximum 1000000000000.0. Lower bound: minimum None, maximum 1000000000000.0. Upper bound: minimum None, maximum 1000000000000.0.
Are these inputs private?

These calculations run in your browser. A shared link contains the values you choose to share. Only questions submitted to the separate AI finder are sent to OpenAI.

Further reading

Method reference ↗

Background reading; this does not imply endorsement or independent review of SumFizz.

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